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    Rights statement: This is the author’s version of a work that was accepted for publication in Computers and Operations Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Operations Research, 67, 2016 DOI: 10.1016/j.cor.2015.09.003

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The multimode covering location problem

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The multimode covering location problem. / Colombo, Fabio; Cordone, Roberto; Lulli, Guglielmo.
In: Computers and Operations Research, Vol. 67, 03.2016, p. 25–33.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Colombo, F, Cordone, R & Lulli, G 2016, 'The multimode covering location problem', Computers and Operations Research, vol. 67, pp. 25–33. https://doi.org/10.1016/j.cor.2015.09.003

APA

Colombo, F., Cordone, R., & Lulli, G. (2016). The multimode covering location problem. Computers and Operations Research, 67, 25–33. https://doi.org/10.1016/j.cor.2015.09.003

Vancouver

Colombo F, Cordone R, Lulli G. The multimode covering location problem. Computers and Operations Research. 2016 Mar;67:25–33. Epub 2015 Sept 21. doi: 10.1016/j.cor.2015.09.003

Author

Colombo, Fabio ; Cordone, Roberto ; Lulli, Guglielmo. / The multimode covering location problem. In: Computers and Operations Research. 2016 ; Vol. 67. pp. 25–33.

Bibtex

@article{3bfdba9c706842c29c4d5147aed18c19,
title = "The multimode covering location problem",
abstract = "In this paper we introduce the Multimode Covering Location Problem. This is a generalization of the Maximal Covering Location Problem that consists in locating a given number of facilities of different types with a limitation on the number of facilities sharing the same site.The problem is challenging and intrinsically much harder than its basic version. Nevertheless, it admits a constant factor approximation guarantee, which can be achieved combining two greedy algorithms. To improve the greedy solutions, we have developed a Variable Neighborhood Search approach, based on an exponential-size neighborhood. This algorithm computes good quality solutions in short computational time. The viability of the approach here proposed is also corroborated by a comparison with a Heuristic Concentration algorithm, which is presently the most effective approach to solve large instances of the Maximal Covering Location Problem.",
keywords = "Maximal covering location problem, Variable neighborhood search, Very large scale neighborhood search, Heuristic concentration",
author = "Fabio Colombo and Roberto Cordone and Guglielmo Lulli",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in Computers and Operations Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Operations Research, 67, 2016 DOI: 10.1016/j.cor.2015.09.003",
year = "2016",
month = mar,
doi = "10.1016/j.cor.2015.09.003",
language = "English",
volume = "67",
pages = "25–33",
journal = "Computers and Operations Research",
issn = "0305-0548",
publisher = "Elsevier Ltd",

}

RIS

TY - JOUR

T1 - The multimode covering location problem

AU - Colombo, Fabio

AU - Cordone, Roberto

AU - Lulli, Guglielmo

N1 - This is the author’s version of a work that was accepted for publication in Computers and Operations Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Operations Research, 67, 2016 DOI: 10.1016/j.cor.2015.09.003

PY - 2016/3

Y1 - 2016/3

N2 - In this paper we introduce the Multimode Covering Location Problem. This is a generalization of the Maximal Covering Location Problem that consists in locating a given number of facilities of different types with a limitation on the number of facilities sharing the same site.The problem is challenging and intrinsically much harder than its basic version. Nevertheless, it admits a constant factor approximation guarantee, which can be achieved combining two greedy algorithms. To improve the greedy solutions, we have developed a Variable Neighborhood Search approach, based on an exponential-size neighborhood. This algorithm computes good quality solutions in short computational time. The viability of the approach here proposed is also corroborated by a comparison with a Heuristic Concentration algorithm, which is presently the most effective approach to solve large instances of the Maximal Covering Location Problem.

AB - In this paper we introduce the Multimode Covering Location Problem. This is a generalization of the Maximal Covering Location Problem that consists in locating a given number of facilities of different types with a limitation on the number of facilities sharing the same site.The problem is challenging and intrinsically much harder than its basic version. Nevertheless, it admits a constant factor approximation guarantee, which can be achieved combining two greedy algorithms. To improve the greedy solutions, we have developed a Variable Neighborhood Search approach, based on an exponential-size neighborhood. This algorithm computes good quality solutions in short computational time. The viability of the approach here proposed is also corroborated by a comparison with a Heuristic Concentration algorithm, which is presently the most effective approach to solve large instances of the Maximal Covering Location Problem.

KW - Maximal covering location problem

KW - Variable neighborhood search

KW - Very large scale neighborhood search

KW - Heuristic concentration

U2 - 10.1016/j.cor.2015.09.003

DO - 10.1016/j.cor.2015.09.003

M3 - Journal article

VL - 67

SP - 25

EP - 33

JO - Computers and Operations Research

JF - Computers and Operations Research

SN - 0305-0548

ER -